Sensor Based Efficient Surface Irrigation System For Improving Water Productivity Using Experimental And Modelling Techniques

The role of hydraulic modeling and soil moisture sensors are very important for productivity enhancement and automation of surface irrigation systems by optimizing field dimensions and timely cutoff of inflow rate. Therefore, this modeling and experimental research was conducted at research site of University of Agriculture, Faisalabad-Pakistan. For this purpose, WinSRFR model and spark fun soil moisture sensor (SEN-13322) were used. After successful calibration of model and sensors, 19 treatments (01 conventional and 18 simulated) were installed in the field included, 2 level of inflow rate (Q(1)=0.0025 and Q(2)=0.0035 m(3)/s), three sensor positions (55, 65 & 75%) along filed length and 3 levels of boarder width (B-1=6.4, B-2 = 8.5 & B-s=10.7m) and for two wheat crop seasons (2016-17 and 2017-18). The results revealed that treatment T-10 (Q(2)S(1)B(1)) has high efficiency and uniformity i.e., application efficiency (AE) = 90%, min. distribution uniformity (DUmin) = 87% and distribution uniformity lower quarter (DUlq)=91, among other treatments. The values of wheat growth parameters were higher in all treatments of Q(2) compared to Q(1). The average minimum amount of water applied was found T-10 (370mm) and achieved maximum water productivity of 14.13 kg/ha/mm compared to control treatment. It was concluded that the significant amount of water was saved along with higher crop yield by optimizing boarder width, cutoff time and inflow rate. It is recommended regional research should be conducted using hydraulic modeling and soil moisture sensors for improving forming output in surface irrigation.